Box-type substation, box-type substation intelligent monitoring method and system

Abstract

The application discloses a box-type transformer substation, a box-type transformer substation intelligent monitoring method and system, and belongs to the technical field of box-type transformer substation intelligent monitoring. The box-type transformer substation intelligent monitoring method and system can significantly improve the operation efficiency of the transformer substation, improve the fault response speed, and reduce the labor cost. Meanwhile, through autonomous learning and optimization, the whole system has good adaptability and is not prone to errors. In addition, the temperature detector is arranged on the pressing block of the transformer, so that the temperature detector can be closer to the heat point of the transformer, the real-time temperature of the transformer can be more accurately monitored, and the transformer is better protected.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of power system automation and control technology, and particularly relates to a box-type substation, a box-type substation intelligent monitoring method and system. BACKGROUND

[0002] The box-type substation is also called an outdoor complete substation, and is also called a combined substation. It is a new type of outdoor complete substation developed in the 1960s and 1970s in western developed countries such as Europe and the United States. It is valued by electric power workers all over the world due to its advantages of flexible combination, convenient transportation, migration and installation, short construction period, low operation cost, no pollution and maintenance-free. In the mid-1990s of the 20th century, simple box-type substations appeared in China and have been rapidly developed.

[0003] In recent years, with the large-scale integration of renewable energy, traditional box-type substations are facing many challenges. These challenges include: 1. Volatility and instability: renewable resources such as wind and solar energy have obvious intermittency and randomness, which causes impact on power grid load; 2. Increased scheduling complexity: more precise load forecasting and real-time scheduling are required to ensure supply and demand balance, thereby avoiding equipment damage caused by overload or lack of load.

[0004] In addition, the existing control system often relies on manual operation, which is not only inefficient but also prone to human errors. At the same time, due to the lack of real-time data monitoring and analysis capabilities, fault handling is slow, which affects the stability of the entire power grid. SUMMARY

[0005] In order to solve the problem that the existing control system often relies on manual operation, which is not only inefficient but also prone to human errors, and lacks real-time data monitoring and analysis capabilities, thereby causing slow fault handling, the present application provides a box-type substation, a box-type substation intelligent monitoring method and system which can have real-time data monitoring and analysis capabilities, and is efficient and less prone to errors.

[0006] The technical solution of the present application is:

[0007] The box-type substation intelligent monitoring method comprises the following steps:

[0008] S1, setting a target state feature:

[0009] Establishing a box-type substation pre-monitoring event type, selecting a target state feature to be monitored according to the box-type substation pre-monitoring event type;

[0010] S2, establishing a target state feature value monitoring model

[0011] Based on the selected target state characteristics, a target state characteristic value monitoring model that needs to be collected is established;

[0012] S3, acquiring target monitoring data

[0013] The target state characteristic value data of the target box-type substation is collected, and the collected target state characteristic value data is substituted into the target state characteristic value monitoring model to calculate and acquire the target monitoring data output based on the target state characteristic value monitoring model;

[0014] S4, establishing a box-type substation event monitoring and abnormality judgment model

[0015] The box-type substation event monitoring and abnormality judgment model is established, which is used to judge whether the box-type substation has operation abnormality and give an abnormality judgment result;

[0016] S5, box-type substation pre-monitoring event judgment and control

[0017] Based on the established box-type substation event monitoring and abnormality judgment model, the judgment result is output, and the corresponding control instruction is given based on the judgment result.

[0018] Further, the target state characteristic value monitoring model in step S2 is constructed as follows:

[0019] Based on the collected target state parameters of the equipment in the box-type substation, a target state parameter feature matrix X of a preset fixed time period of the target box-type substation is established;

[0020] The target state parameter feature matrix X is specifically expressed as follows:

[0021] X ;

[0022] Wherein, the target feature matrix X represents a target state parameter data set with a fixed time interval as a time unit in a fixed time period , represents the first characteristic value of the target state parameter collected according to the first data collection rule in each time unit, represents the second characteristic value of the target state parameter collected according to the second data collection rule in each time unit, and n represents the number n of time units in each fixed time period .

[0023] Further, in step S3, the target state characteristic value data of the target box-type substation is collected, specifically in each time unit At the end time, the target state parameter value is collected once and used as the first feature value of the target state parameter. Perform data storage;

[0024] In each time interval Further according to the predetermined time interval Collect the target state parameter values, and use the sum of the accumulated target state parameter values ​​as the second characteristic value of the target state parameter. ;

[0025] After accumulating n rounds of data collection, the target state parameter feature matrix X is finally formed.

[0026] Furthermore, step S4 establishes an event monitoring and anomaly detection model for prefabricated substations, including the following sub-steps:

[0027] S41: Establish an event monitoring and early warning judgment function for the prefabricated substation. The early warning judgment function is expressed as follows:

[0028] ,

[0029] in This is the final warning judgment value. For a fixed time period The sum of the second eigenvalues ​​collected internally. For the target device in each fixed time period The threshold value of the second characteristic value that enables normal operation within the system, where The specific expression is as follows:

[0030]

[0031] S42: Establish anomaly detection rules

[0032] The system terminal acquires the first feature value of the collected target state parameters in real time. , with the first feature security threshold Comparison, when the system detects a fixed time period The first eigenvalue appears twice consecutively. > If so, it is determined that there is a potential operational anomaly;

[0033] within a fixed time period Within the system terminal, the final warning judgment value is obtained. ,when If the value is greater than 1, then an anomaly is determined to exist.

[0034] Further, in step S5, based on the established box-type substation event monitoring and abnormality judgment model, a judgment result is output, and corresponding control instructions are given based on the judgment result, specifically including:

[0035] When it is judged that there is a potential operation abnormality, the control terminal automatically gives a pre-warning prompt for the potential abnormality in the monitoring event, the staff performs abnormality checking work for the pre-monitoring event, confirms whether the monitoring event truly has an abnormality, and gives a final conclusion;

[0036] When it is judged that there is an operation abnormality, the control terminal automatically gives a pre-warning prompt for the abnormality in the monitoring event, the system automatically sends corresponding countermeasures to the staff, and the staff performs abnormality checking and abnormality disposal for the pre-monitoring event.

[0037] Further, the pre-monitoring event type includes whether the temperature of the transformer room in the box-type substation is abnormal, whether the temperature near the high-voltage and low-voltage terminals of the transformer is abnormal, and the state features that need to be monitored include the temperature value of the transformer room or the temperature value near the high-voltage and low-voltage terminals of the transformer.

[0038] Further, the pre-monitoring event type is whether the temperature of the transformer room in the box-type substation is abnormal, the fixed time period is one week, the fixed time interval is 1 hour, the target state parameter data set of the time unit is the real-time temperature value of the transformer room collected once every 1 hour as the first characteristic value , and the real-time temperature of the transformer room is collected every 1 hour with as the second time interval, the real-time temperature is added for 60 times to obtain the second characteristic value , and n=168.

[0039] The application also provides a box-type substation intelligent monitoring system, which is used for executing the box-type substation intelligent monitoring method and includes:

[0040] A data collection module is used for collecting the target state characteristic value data of each target device in the box-type substation in real time, and sending the collected data information to a data processing and judgment module;

[0041] The data processing and judgment module is used for performing data processing on the collected data and giving an abnormality judgment result;

[0042] A control terminal is used for giving a control instruction based on the judgment result given by the data processing and judgment module and performing corresponding control processing.

[0043] The application further provides a box-type substation provided with the box-type substation intelligent monitoring system, and the box-type substation comprises a box body, a high-voltage cabinet, a low-voltage cabinet, a transformer, a plurality of heat dissipation devices and a transformer temperature controller, the high-voltage cabinet, the low-voltage cabinet and the transformer are arranged in the box body, the high-voltage cabinet is located on one side of the low-voltage cabinet and the transformer, the transformer is arranged above the low-voltage cabinet, the low-voltage cabinet is provided with an operation panel, the transformer temperature controller is arranged on the operation panel of the low-voltage cabinet, the heat dissipation devices are inlaid on the surface of the box body, and the heat dissipation devices are located beside the transformer, a plurality of pressing blocks and a plurality of temperature detectors are arranged on the transformer, each temperature detector is arranged in the pressing block, the temperature detectors and the heat dissipation devices are electrically connected to the transformer temperature controller, and the transformer temperature controller is communicatively connected to the box-type substation intelligent monitoring system.

[0044] The pressing block is provided with a groove, the temperature detector is arranged in the groove, the transformer temperature controller is provided with an RS485 communication interface, and the RS485 communication interface is connected to the box-type substation intelligent monitoring system.

[0045] The application has the following beneficial effects:

[0046] By implementing the box-type substation intelligent monitoring method and system, the operation efficiency of the substation can be improved, the fault response speed can be improved, and the labor cost can be reduced; meanwhile, through autonomous learning and optimization, the whole system has good adaptability and is not prone to errors; in addition, the temperature detector is arranged on the pressing block of the transformer, so that the temperature detector can be closer to the heating point of the transformer, the real-time temperature of the transformer can be more accurately monitored, and the transformer can be better protected. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The figure is a flowchart of the box-type substation intelligent monitoring method of the application;

[0048] Figure 2 The figure is a front view structural schematic diagram of the box-type substation of the application;

[0049] Figure 3 The figure is a rear view structural schematic diagram of the box-type substation of the application;

[0050] Figure 4 The figure is a structural schematic diagram of the transformer of the box-type substation of the application;

[0051] Figure 5 The figure is a sectional view structural schematic diagram of the transformer of the box-type substation of the application;

[0052] Reference numerals: 1, box, 2, high voltage cabinet, 3, low voltage cabinet, 31, operation panel, 4, transformer, 41, pressure block, 411, groove, 42, temperature detector, 5, heat dissipation device, 6, transformer temperature controller. DETAILED DESCRIPTION

[0053] In order to make the technical problems to be solved by the present application, technical solutions and beneficial effects more clear, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0054] Example 1

[0055] Please refer to Figure 1 The present application provides a box-type substation intelligent monitoring method, comprising the following steps:

[0056] S1, setting target state characteristics:

[0057] Establishing the box-type substation pre-monitoring event type, selecting the target state characteristics to be monitored according to the box-type substation pre-monitoring event type;

[0058] S2, establishing target state characteristic value monitoring model

[0059] Based on the selected target state characteristics, the target state characteristic value monitoring model to be collected is established;

[0060] S3, obtaining target monitoring data

[0061] Collecting the target state characteristic value data of the target box-type substation, substituting the collected target state characteristic value data into the target state characteristic value monitoring model, and calculating to obtain the target monitoring data output based on the target state characteristic value monitoring model;

[0062] S4, establishing box-type substation event monitoring and abnormality judgment model

[0063] Establishing a box-type substation event monitoring and abnormality judgment model, which is used to judge whether the box-type substation has running abnormality and give abnormality judgment result;

[0064] S5, box-type substation pre-monitoring event judgment and control

[0065] Based on the established box-type substation event monitoring and abnormality judgment model, the judgment result is output, and the corresponding control instruction is given based on the judgment result.

[0066] Further, the specific construction method of the target state characteristic value monitoring model in step S2 is as follows:

[0067] Based on the collected target state parameters of the equipment in the box-type substation, a preset fixed time period for the target box-type substation is established The target state parameter feature matrix X is established.

[0068] The target state parameter feature matrix X is expressed as follows:

[0069] X ;

[0070] Wherein, the target feature matrix X represents the target state parameter data set with fixed time interval as the time unit in the fixed time period , represents the first feature value of the target state parameter collected according to the first data collection rule in each time unit, represents the second feature value of the target state parameter collected according to the second data collection rule in each time unit, and n represents the number n of time units in each fixed time period .

[0071] Further, in step S3, the target state feature value data of the target box-type substation is collected, which is specifically the target state parameter value collected once at the end of each time unit as the first feature value of the target state parameter for data storage;

[0072] In each time interval , the target state parameter value is further collected according to the predetermined time interval , and the sum of the accumulated target state parameter values is taken as the second feature value of the target state parameter .

[0073] The n rounds of accumulation are collected, and finally the target state parameter feature matrix X is formed.

[0074] Further, in step S4, the box-type substation event monitoring and abnormality judgment model is established, including the following substeps:

[0075] S41: Establishing a box-type substation event monitoring and early warning judgment function, which is expressed as follows:

[0076] ,

[0077] Wherein is the final early warning judgment value, is the sum of the second feature values collected in the fixed time period , ​a second characteristic value sum threshold value that the target device can normally operate within each fixed time period , wherein is specifically expressed as follows:

[0078]

[0079] S42: Establish an abnormality judgment rule

[0080] The system terminal acquires the first characteristic value of the collected target state parameter in real time , and compares it with the first characteristic safety threshold value When the system monitors that the first characteristic value appears twice in succession within a fixed time period ,it is determined that there is a potential operation abnormality;

[0081] Within a fixed time period , the system terminal acquires the final early warning judgment value When > 1, it is determined that there is an abnormality.

[0082] Preferably, in step S5, based on the established box-type substation event monitoring and abnormality judgment model, the judgment result is output, and corresponding control instructions are given based on the judgment result, specifically including:

[0083] When it is determined that there is a potential operation abnormality, the control terminal automatically gives a pre-warning prompt that there is a potential abnormality in the monitoring event, the staff performs abnormality investigation work on the pre-monitoring event, confirms whether the monitoring event truly has an abnormality, and gives a final conclusion;

[0084] When it is determined that there is an operation abnormality, the control terminal automatically gives a pre-warning prompt that the monitoring event has an abnormality, the system automatically sends corresponding countermeasures to the staff, and the staff performs abnormality investigation and abnormality disposal on the pre-monitoring event.

[0085] Preferably, the pre-monitoring event type includes whether the temperature of the transformer room in the box-type substation is abnormal, whether the temperature near the high and low voltage terminals of the transformer is abnormal, and the state characteristics that need to be monitored include the temperature value of the transformer room or the temperature value near the high and low voltage terminals of the transformer.

[0086] In the preferred embodiment, the pre-monitoring event type is whether the temperature of the transformer room in the box-type substation is abnormal, the fixed time period is one week, the fixed time interval is 1 hour, the target state parameter data set of the time unit is randomly collected once every 1 hour the real-time temperature value of the transformer room as the first characteristic value , and the temperature value of the transformer room is acquired every 1 hour Collect the real-time temperature of the transformer room for a second time interval, and add the real-time temperatures for 60 times to obtain a second characteristic value , n = 168. The specific pre-monitoring event type can be customized according to actual monitoring needs, and the target state parameters, the first characteristic value, the second characteristic value, and the like specific physical quantity types are confirmed, and the first time interval and the second time interval are customized according to actual monitoring needs. The embodiment only gives an exemplary description, and will not be described one by one.

[0087] In this feature matrix, each row corresponds to a time point (every hour), and each column corresponds to a specific feature. Through such a structured way, the original data can be converted into a format suitable for machine learning algorithm processing, so as to carry out subsequent analysis and prediction. This method enables the model to identify the relationship between time and power load, providing a basis for adjusting the strategy.

[0088] Embodiment 2

[0089] The application also provides a box-type substation intelligent monitoring system, which is used to execute the box-type substation intelligent monitoring method described above, and comprises:

[0090] which is used to execute the box-type substation intelligent monitoring method, and comprises:

[0091] A data acquisition module is configured to acquire the target state characteristic value data of each target device in the box-type substation in real time, and send the acquired data information to the data processing and judgment module.

[0092] A data processing and judgment module is configured to process the acquired data and give an abnormality judgment based on the data processing result.

[0093] A control terminal is configured to give a control instruction based on the judgment result given by the data processing and judgment module, and perform corresponding control processing.

[0094] In summary, by implementing the box-type substation intelligent monitoring method and system, the operation efficiency of the substation can be significantly improved, the fault response speed can be improved, and the labor cost can be reduced. At the same time, through autonomous learning and optimization, the entire system has good adaptability and is not prone to errors.

[0095] Embodiment 3

[0096] The temperature control device of the existing box-type substation transformer mostly uses the temperature of the transformer room or the temperature near the high and low voltage terminals of the transformer as the starting condition of the heat dissipation equipment. However, the main heat generating parts of the transformer are the iron core and the coil. Therefore, the internal heat dissipation system of the box-type substation has certain defects in the use scene of the charging station.

[0097] Referring to Figures 2-5 The application further discloses a box-type transformer substation connected with the box-type transformer substation intelligent monitoring system, which comprises a box body 1, a high-voltage cabinet 2, a low-voltage cabinet 3, a transformer 4, a plurality of heat dissipation devices 5 and a transformer temperature controller 6, referring to Figure 3 The heat dissipation device 5 is a fan, the high-voltage cabinet 2, the low-voltage cabinet 3 and the transformer 4 are arranged in the box body 1, the high-voltage cabinet 2 is located on one side of the low-voltage cabinet 3 and the transformer 4, the transformer 4 is arranged above the low-voltage cabinet 3, the low-voltage cabinet 3 is provided with an operation panel 31, the transformer temperature controller 6 is arranged on the operation panel 31 of the low-voltage cabinet 3, the heat dissipation device 5 is inlaid on the surface of the box body 1 and located beside the transformer 4, the transformer 4 is provided with a plurality of pressing blocks 41 and a plurality of temperature detectors 42, the pressing blocks 41 are made of insulating materials and used for fixing coils, and each phase of the transformer 4 is provided with nine pressing blocks 41, each temperature detector 42 is arranged in the pressing block 41, the temperature detector 42 and the heat dissipation device 5 are electrically connected with the transformer temperature controller 6, the transformer temperature controller 6 is communicatively connected with the box-type transformer substation intelligent monitoring system, the transformer temperature controller 6 mainly receives signals from the temperature detector 42, controls the start of the heat dissipation device 5, and sends an alarm and tripping to the high-voltage cabinet 2; after the transformer temperature controller 6 receives the signals from the temperature detector 42, a signal is sent to start the heat dissipation device 5 as long as the temperature of any place reaches the setting value of the fan; when the temperature detector 42 detects that the temperature of any place reaches the high-temperature alarm setting value or the over-temperature tripping setting value, the transformer temperature controller 6 sends a signal to the relay protection device or the opening coil of the high-voltage cabinet 2 to perform a related setting action.

[0098] Further, the pressing block 41 is provided with a groove 411, and the temperature detector 42 is arranged in the groove 411, so that the temperature detector 42 can be closer to the heat point of the transformer 4, the real-time temperature of the transformer 4 can be more accurately monitored, and the transformer 4 can be better protected.

[0099] Further, the transformer temperature controller 6 is provided with an RS485 communication interface, and is connected with the box-type transformer substation intelligent monitoring system through the RS485 communication interface, so that the temperature change of a key part of the transformer can be comprehensively monitored.

[0100] The above embodiment only expresses one implementation of the present application, which is described in more detail and in more detail, but cannot be understood as limiting the scope of the patent of the present application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for intelligent monitoring of prefabricated substations, characterized in that, Includes the following steps: S1. Set target state characteristics Establish the types of pre-monitoring events for prefabricated substations, and select the target status characteristics that need to be monitored based on these types of events. S2. Establish a target state characteristic value monitoring model. Based on the selected target state characteristics, a monitoring model for the target state characteristic values ​​to be collected is established. The specific construction method is as follows: Based on the collected target state parameters of the equipment inside the prefabricated substation, a preset fixed time period is established for the target prefabricated substation. The target state parameter feature matrix X within; The target state parameter feature matrix X is specifically expressed as follows: X ； Wherein, the target feature matrix X represents the feature matrix within a fixed time period. Within a fixed time interval This is the target state parameter dataset for the time unit. Representative in each The first characteristic value of the target state parameter collected within the time unit according to the first data acquisition rule. Representative in each The second characteristic value of the target state parameter collected within the time unit according to the second data acquisition rule, where n represents each fixed time period. Inner Time Unit The quantity n; S3. Obtain target monitoring data Collect target state characteristic value data of the target box-type substation, substitute the collected target state characteristic value data into the target state characteristic value monitoring model, and calculate and obtain the target monitoring data based on the output of the target state characteristic value monitoring model; S4. Establish an event monitoring and anomaly detection model for prefabricated substations. A model for monitoring and judging events in prefabricated substations is established. This model is used to determine whether there are operational anomalies in the prefabricated substations and to provide anomaly judgment results. The model includes the following sub-steps: S41: Establish an event monitoring and early warning judgment function for the prefabricated substation. The early warning judgment function is expressed as follows: ， in This is the final warning judgment value. For a fixed time period The sum of the second eigenvalues ​​collected internally. For the target device in each fixed time period The threshold value of the second characteristic value that enables normal operation within the system, where The specific expression is as follows: S42: Establish anomaly detection rules The system terminal acquires the first feature value of the collected target state parameters in real time. , with the first feature security threshold Comparison, when the system detects a fixed time period The first eigenvalue appears twice consecutively. > If so, it is determined that there is a potential operational anomaly; within a fixed time period Within the system terminal, the final warning judgment value is obtained. ,when If the value is greater than 1, then an anomaly is determined to exist; S5, Pre-monitoring event judgment and control of prefabricated substations Based on the established event monitoring and anomaly judgment model for prefabricated substations, the judgment results are output, and corresponding control commands are given based on the judgment results.

2. The intelligent monitoring method for prefabricated substations according to claim 1, characterized in that: In step S3, the target state characteristic value data of the target box-type substation is collected, specifically in each time unit. At the end time, the target state parameter value is collected once and used as the first feature value of the target state parameter. Perform data storage; In each time interval Further according to the predetermined time interval Collect the target state parameter values, and use the sum of the accumulated target state parameter values ​​as the second characteristic value of the target state parameter. ; After accumulating n rounds of data collection, the target state parameter feature matrix X is finally formed.

3. The intelligent monitoring method for prefabricated substations according to claim 2, characterized in that: In step S5, based on the established event monitoring and anomaly judgment model for the prefabricated substation, the judgment result is output, and the corresponding control command is given based on the judgment result, specifically including: When a potential operational anomaly is detected, the control terminal automatically issues an early warning prompt indicating the presence of a potential anomaly in the monitored event. Staff then conduct anomaly investigation on the pre-monitored event to confirm whether the monitored event is indeed abnormal and provide a final conclusion. When an operational anomaly is detected, the control terminal automatically issues an early warning of the abnormality in the monitored event. The system automatically sends corresponding countermeasures to the staff, who then conduct anomaly investigation and handling for the pre-monitored event.

4. The intelligent monitoring method for prefabricated substations according to any one of claims 1-3, characterized in that: The types of pre-monitored events include whether the temperature in the transformer room of the prefabricated substation is abnormal, and whether the temperature near the high and low voltage terminals of the transformer is abnormal. The status characteristics that need to be monitored include the temperature value of the transformer room or the temperature value near the high and low voltage terminals of the transformer.

5. The intelligent monitoring method for prefabricated substations according to claim 4, characterized in that: The pre-monitoring event type is whether the temperature in the transformer room of the prefabricated substation is abnormal, with a fixed time period. One week, fixed time interval The target state parameter dataset is for a 1-hour time unit. The real-time temperature value of the transformer room is randomly collected once every 1 hour as the first feature value. and every hour The real-time temperature of the transformer room was collected at the second time interval. Sixty data points were collected, and the real-time temperatures were summed to obtain the second characteristic value. n=168.

6. A prefabricated substation intelligent monitoring system, characterized in that, It is used to perform the intelligent monitoring method for prefabricated substations according to any one of claims 1-5, comprising: The data acquisition module is used to collect target status characteristic value data of each target device in the box-type substation in real time, and send the collected data information to the data processing and judgment module. The data processing and judgment module is used to process the collected data and make anomaly judgments based on the data processing results. The control terminal, based on the judgment result given by the data processing and judgment module, issues control commands and performs corresponding control processing.

7. A prefabricated substation, characterized in that, The system is equipped with the intelligent monitoring system for a prefabricated substation as described in claim 6, comprising: a prefabricated enclosure, a high-voltage switchgear, a low-voltage switchgear, a transformer, several heat dissipation devices, and a transformer temperature controller. The high-voltage switchgear, the low-voltage switchgear, and the transformer are all housed within the enclosure. The high-voltage switchgear is located on one side of the low-voltage switchgear and the transformer, and the transformer is located above the low-voltage switchgear. The low-voltage switchgear has an operation panel, and the transformer temperature controller is located on the operation panel of the low-voltage switchgear. The heat dissipation devices are embedded in the surface of the enclosure and are located beside the transformer. The transformer has several pressure blocks and several temperature detectors, each of which is located within a pressure block. The temperature detectors and the heat dissipation devices are electrically connected to the transformer temperature controller, and the transformer temperature controller is communicatively connected to the intelligent monitoring system for the prefabricated substation.

8. The prefabricated substation according to claim 7, characterized in that, The pressure block is provided with a groove, the temperature detector is located in the groove, and the transformer temperature controller is provided with an RS485 communication interface, which is connected to the intelligent monitoring system of the box-type substation.

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